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At least 217 records · Page 12

Hail Storm Risk Assessment Using Space-Borne Remote Sensing Observations and Reanalyses

Much of the world is impacted by severe thunderstorms, but whether they become disasters depends upon resilience--our capacity to prepare, mitigate, respond, and recover. Hail is the costliest severe weather hazard for the insurance industry, generating ~70% of severe convective storm losses due to damage to assets such as homes, businesses, agriculture, and infrastructure. Most insurance companies do not reserve enough capital to cover catastrophes, so they acquire reinsurance. The reinsurance industry uses catastrophe models (CatModels) to statistically estimate risk to an insurer’s portfolio. Hail CatModels are developed with climatologies that define hailstorm frequency and severity. Hail-prone areas can be defined using hail reports from trained spotters, the media, and the general public. Extremely severe hail (2+ inch diameter) occurs nearly every day across the world. Weather radars can detect hail because hailstones strongly reflect microwave signals that they emit. However, hail climatologies are difficult to derive because hail covers small areas and there are neither hail reporting mechanisms (e.g. website or mobile app) nor radar networks in most places outside the US and Europe. This lack of ground truth on severe hail puts society and economies at risk. Hail is generated within storms by strong updrafts. These updrafts exhibit unique signatures in NASA and other agency satellite observations, offering new opportunities for hailstorm analysis. Geostationary (GEO) visible and infrared imagery has been collected for ~15-25 years across the world (region dependent) and methods have been developed at NASA Langley Research Center (LaRC) to detect hailstorm updrafts using GEO imagery. Climatological GEO updraft data has been used by Willis Towers Watson (WTW), a leader in catastrophe risk assessment for the insurance industry, and Karlsruhe Institute of Technology to develop CatModels over Europe and Australia. Hail can also be inferred with passive microwave imagery collected by low-Earth-orbiting sensors such as the GPM GMI, TRMM TMI, AMSR-E, AMSR-2, SSM/I, and SSMIS over the last 20+ years using methods developed at the Marshall Space Flight Center (MSFC). Hailstorms generate enhanced lightning flash rates that can be tracked using new GOES-R series GEO Lightning Mapping (GLM) imagery. Atmospheric reanalyses can be used to define favorable hailstorm environments for combination with the satellite-based storm detections. This presentation will describe a framework for developing continental to global hail climatologies and CatModels based on NASA satellite data and capabilities. This is a collaboration between LaRC and MSFC, WTW, and partners in Brazil, Argentina, and South Africa. This project seeks to mitigate hail disasters by aiding development of new satellite-based severe storm nowcasting tools by regional partners and developing climatologies to improve societal understanding of hail frequency. GEOO visible and infrared metrics of storm intensity, environmental conditions based on reanalyses, spotter hail reports and radar MESH observations are intercompared to quantify the detectability of hailstorms, and our ability to discriminate hailstorms from other severe storms. We are also maturing methods using land surface imaging satellite data (e.g. MODIS, Landsat, Sentinel 1 and 2) to identify hail damage to agriculture. Work with WTW will improve socioeconomic resilience through development of new CatModels. Southern Brazil, Uruguay, Paraguay, and Argentina feature some of the most intense thunderstorms on Earth. South America and South Africa are developing insurance markets of interest to WTW clients, and is similar to other regions routinely impacted by hail that do not have comprehensive hail reporting or radars to assess hailstorm frequency. Project datasets will be made available via online GIS-enabled tools developed at the LaRC Atmospheric Science Data Center (ASDC) which will visualize data and provide it in multiple formats for use in a wide range of open source and commercial tools.

Kristopher Michael Bedka↗

Advances in Entry Modeling for Impact Risk Assessment

A summary of recent advancements in the detailed modeling of asteroid atmospheric entry processes made through NASA’s Asteroid Threat Assessment Project (ATAP) is presented. Understanding, and accurately modeling these processes and their associated uncertainties is critical to predicting all downstream impact effects, such as blast wave and thermal damage footprints. Furthermore, there is (perhaps thankfully) a dearth of empirical data for large impactors of the kind that would pose a threat to human populations, on which to anchor and/or validate models used in risk assessments. Therefore, we must rely heavily on detailed theoretical and numerical modeling to develop robust assessments for decision makers. To that end, ATAP has made some significant progress in advancing the capabilities in this area. Two areas in particular are highlighted in the present work: meteoroid ablation mechanisms, and bolide luminosity.

ATAP↗

International Space Station End-of-Life Probabilistic Risk Assessment

The International Space Station (ISS) end‐of‐life (EOL) cycle is currently scheduled for 2020, although there are ongoing efforts to extend ISS life cycle through 2028. The EOL for the ISS will require deorbiting the ISS. This will be the largest manmade object ever to be de‐orbited therefore safely deorbiting the station will be a very complex problem. This process is being planned by NASA and its international partners. Numerous factors will need to be considered to accomplish this such as target corridors, orbits, altitude, drag, maneuvering capabilities etc. The ISS EOL Probabilistic Risk Assessment (PRA) will play a part in this process by estimating the reliability of the hardware supplying the maneuvering capabilities. The PRA will model the probability of failure of the systems supplying and controlling the thrust needed to aid in the de‐orbit maneuvering.

Duncan, Gary W.↗

The Galileo single-event upset solution and risk assessment

The Galileo probe will be subject to radiation fields and energetic particle bombardment during its outward bound journey and in orbit around Jupiter and its moons. To avoid the occurrence and propagation of effects of single event upset (SEU) bit state changes induced by the bombardments attempts were made to harden the Galileo electronics against SEUs. The hazards are especially acute for Schottky diode and low-power Schottky TTL parts. The preventive action options which were scheduled are reviewed, noting the selection of CMOS chips as replacements for SEU-susceptible devices. The simulation and risk assessment that were performed to evaluate the potential success of the replacements are summarized, with emphasis on the data employed to ensure the accuracy of the assessments and the predicted effects of SEUs in the various Galileo subsystems.

Burdick, Garry M.↗

Radiation exposure and risk assessment for critical female body organs

Space radiation exposure limits for astronauts are based on recommendations of the National Council on Radiation Protection and Measurements. These limits now include the age at exposure and sex of the astronaut. A recently-developed computerized anatomical female (CAF) model is discussed in detail. Computer-generated, cross-sectional data are presented to illustrate the completeness of the CAF model. By applying ray-tracing techniques, shield distribution functions have been computed to calculate absorbed dose and dose equivalent values for a variety of critical body organs (e.g., breasts, lungs, thyroid gland, etc.) and mission scenarios. Specific risk assessments, i.e., cancer induction and mortality, are reviewed.

Atwell, William↗

International Space Station End-of-Life Probabilistic Risk Assessment

Although there are ongoing efforts to extend the ISS life cycle through 2028, the International Space Station (ISS) end-of-life (EOL) cycle is currently scheduled for 2020. The EOL for the ISS will require de-orbiting the ISS. This will be the largest manmade object ever to be de-orbited, therefore safely de-orbiting the station will be a very complex problem. This process is being planned by NASA and its international partners. Numerous factors will need to be considered to accomplish this such as target corridors, orbits, altitude, drag, maneuvering capabilities, debris mapping etc. The ISS EOL Probabilistic Risk Assessment (PRA) will play a part in this process by estimating the reliability of the hardware supplying the maneuvering capabilities. The PRA will model the probability of failure of the systems supplying and controlling the thrust needed to aid in the de-orbit maneuvering.

Duncan, Gary↗

Post-Challenger evaluation of space shuttle risk assessment and management

As the shock of the Space Shuttle Challenger accident began to subside, NASA initiated a wide range of actions designed to ensure greater safety in various aspects of the Shuttle system and an improved focus on safety throughout the National Space Transportation System (NSTS) Program. Certain specific features of the NASA safety process are examined: the Critical Items List (CIL) and the NASA review of the Shuttle primary and backup units whose failure might result in the loss of life, the Shuttle vehicle, or the mission; the failure modes and effects analyses (FMEA); and the hazard analysis and their review. The conception of modern risk management, including the essential element of objective risk assessment is described and it is contrasted with NASA's safety process in general terms. The discussion, findings, and recommendations regarding particular aspects of the NASA STS safety assurance process are reported. The 11 subsections each deal with a different aspect of the process. The main lessons learned by SCRHAAC in the course of the audit are summarized.

Source record↗

Independent Review of U.S. and Russian Probabilistic Risk Assessments for the International Space Station Mini Research Module #2 Micrometeoroid and Orbital Debris Risk

The Mini-Research Module-2 (MRM-2), a Russian module on the International Space Station, does not meet its requirements for micrometeoroid and orbital debris probability of no penetration (PNP). To document this condition, the primary Russian Federal Space Agency ISS contractor, S.P. Korolev Rocket and Space Corporation-Energia (RSC-E), submitted an ISS non-compliance report (NCR) which was presented at the 5R Stage Operations Readiness Review (SORR) in October 2009. In the NCR, RSC-E argued for waiving the PNP requirement based on several factors, one of which was the risk of catastrophic failure was acceptably low at 1 in 11,100. However, NASA independently performed an assessment of the catastrophic risk resulting in a value of 1 in 1380 and believed that the risk at that level was unacceptable. The NASA Engineering and Safety Center was requested to evaluate the two competing catastrophic risk values and determine which was more accurate. This document contains the outcome of the assessment.

Squire, Michael D.↗

Miniature Biosensor with Health Risk Assessment Feedback

Heart rate (HR) monitoring is a medical requirement during exercise on the International Space Station (ISS), fitness tests, and extravehicular activity (EVA); however, NASA does not currently have the technology to consistently and accurately monitor HR and other physiological data during these activities. Performance of currently available HR monitor technologies is dependent on uninterrupted contact with the torso and are prone to data drop-out and motion artifact. Here, we seek an alternative to the chest strap and electrode based sensors currently in use on ISS today. This project aims to develop a high performance, robust earbud based biosensor with focused efforts on improved HR data quality during exercise or EVA. A health risk assessment algorithm will further advance the goals of autonomous crew health care for exploration missions.

Hanson, Andrea↗

The Flight Dynamics Risk Assessment of Artemis I

With launch vehicles and spacecraft, it is necessary to dynamically test the structure to validate structural models. These validated models are then used to determine a launch vehicle's control stability margin and the loads on the structure. While often a dedicated structural test article is used to correlate the integrated structure in preparation for the final analysis cycles, the Artemis I flight is using an approach where the components of the launch vehicle are dynamically tested and the component models validated. The fully integrated vehicle is not tested until a few months before launch, which limits the ability to fully correlate a model prior to launch. This paper introduces the Flight Dynamics Risk Assessment of the vehicle, which is the process being used to determine the adequacy of the vehicle structural model after the Integrated Modal Test. This work outlines the process of quickly tuning a model post-test then determining any control margin violations and increases in loads due to that tuned model.

Eric C Stewart↗

The Flight Dynamics Risk Assessment of Artemis I

With launch vehicles and spacecraft, it is necessary to dynamically test the structure to validate structural models. These validated models are then used to determine a launch vehicle's control stability margin and the loads on the structure. While often a dedicated structural test article is used to correlate the integrated structure in preparation for the final analysis cycles, the Artemis I flight is using an approach where the components of the launch vehicle are dynamically tested and the component models validated. The fully integrated vehicle is not tested until a few months before launch, which limits the ability to fully correlate a model prior to launch. This paper introduces the Flight Dynamics Risk Assessment of the vehicle, which is the process being used to determine the adequacy of the vehicle structural model after the Integrated Modal Test. This work outlines the process of quickly tuning a model post-test then determining any control margin violations and increases in loads due to the tuning of the model.

Eric C Stewart↗

Radiation Beamline Testbeds for the Simulation of Planetary and Spacecraft Environments for Human and Robotic Mission Risk Assessment

The Center for Radiation Engineering and Science for Space Exploration (CRESSE) at Prairie View A&M University, Prairie View, Texas, USA, is establishing an integrated, multi-disciplinary research program on the scientific and engineering challenges faced by NASA and the international space community caused by space radiation. CRESSE focuses on space radiation research directly applicable to astronaut health and safety during future long term, deep space missions, including Martian, lunar, and other planetary body missions beyond low earth orbit. The research approach will consist of experimental and theoretical radiation modeling studies utilizing particle accelerator facilities including: 1. NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratory; 2. Proton Synchrotron at Loma Linda University Medical Center; and 3. Los Alamos Neutron Science Center (LANSCE) at Los Alamos National Laboratory. Specifically, CRESSE investigators are designing, developing, and building experimental test beds that simulate the lunar and Martian radiation environments for experiments focused on risk assessment for astronauts and instrumentation. The testbeds have been designated the Bioastronautics Experimental Research Testbeds for Environmental Radiation Nostrum Investigations and Education (BERT and ERNIE). The designs of BERT and ERNIE will allow for a high degree of flexibility and adaptability to modify experimental configurations to simulate planetary surface environments, planetary habitats, and spacecraft interiors. In the nominal configuration, BERT and ERIE will consist of a set of experimental zones that will simulate the planetary atmosphere (Solid CO2 in the case of the Martian surface.), the planetary surface, and sub-surface regions. These experimental zones can be used for dosimetry, shielding, biological, and electronic effects radiation studies in support of space exploration missions. BERT and ERNIE are designed to be compatible with the experimental areas associated with the above facilities. CRESSE has broad expertise in space radiation in the areas of space radiation environment modeling, Monte-Carlo radiation transport modeling, space radiation instrumentation and dosimetry, radiation effects on electronics, and multi-functional composite shielding materials. The BERT and ERNIE testbeds will be utilized in individual and collaborative research incorporating this expertise. The research goal is to maximize the technical readiness level (TRL) of radiation instrumentation for human and robotic missions, optimizing the return value of CRESSE for NASA exploration and international co-operative missions. Outcomes and knowledge from research utilizing BERT and ERNIE will be applied to a variety of scientific and engineering disciplines vital for safe and reliable execution of future space exploration missions, which can be negatively impacted by the space radiation environment. The testbeds will be central to a variety of university educational activities and educational goals of NASA. Specifically, BERT and ERNIE will enhance educational opportunities in science, technology, engineering and mathematics (STEM) disciplines for engineering and science students at PVAMU, a historically black college/university. Preliminary data on prototype testbed configurations, including simulated lunar regolith (JSC-1A stimulant based on Apollo 11 samples), regolith/polyethylene composites, and dry ice, will be presented to demonstrate the usefulness of BERT and ERNIE in radiation beam line experiments.

Wilkins, Richard↗

Risk Assessment Update: Russian Segment

BUMPER-II version 1.95j source code was provided to RSC-E- and Khrunichev at January 2012 MMOD TIM in Moscow. MEMCxP and ORDEM 3.0 environments implemented as external data files. NASA provided a sample ORDEM 3.0 g."key" & "daf" environment file set for demonstration and benchmarking BUMPER -II v1.95j installation at the Jan-12 TIM. ORDEM 3.0 has been completed and is currently in beta testing. NASA will provide a preliminary set of ORDEM 3.0 ".key" & ".daf" environment files for the years 2012 through 2028. Bumper output files produced using the new ORDEM 3.0 data files are intended for internal use only, not for requirements verification. Output files will contain these words ORDEM FILE DESCRIPTION = PRELIMINARY VERSION: not for production. The projectile density term in many BUMPER-II ballistic limit equations will need to be updated. Cube demo scripts and output files delivered at the Jan-12 TIM have been updated for the new ORDEM 3.0 data files. Risk assessment results based on ORDEM 3.0 and MEM will be presented for the Russian Segment (RS) of ISS.

Christiansen, Eric↗

Monte Carlo Simulation of Markov, Semi-Markov, and Generalized Semi- Markov Processes in Probabilistic Risk Assessment

A standard tool of reliability analysis used at NASA-JSC is the event tree. An event tree is simply a probability tree, with the probabilities determining the next step through the tree specified at each node. The nodal probabilities are determined by a reliability study of the physical system at work for a particular node. The reliability study performed at a node is typically referred to as a fault tree analysis, with the potential of a fault tree existing.for each node on the event tree. When examining an event tree it is obvious why the event tree/fault tree approach has been adopted. Typical event trees are quite complex in nature, and the event tree/fault tree approach provides a systematic and organized approach to reliability analysis. The purpose of this study was two fold. Firstly, we wanted to explore the possibility that a semi-Markov process can create dependencies between sojourn times (the times it takes to transition from one state to the next) that can decrease the uncertainty when estimating time to failures. Using a generalized semi-Markov model, we studied a four element reliability model and were able to demonstrate such sojourn time dependencies. Secondly, we wanted to study the use of semi-Markov processes to introduce a time variable into the event tree diagrams that are commonly developed in PRA (Probabilistic Risk Assessment) analyses. Event tree end states which change with time are more representative of failure scenarios than are the usual static probability-derived end states.

English, Thomas↗

Chile Wildland Fires: Augmenting Wildfire Risk Assessment Efforts with Satellite-based Measurements of Soil Moisture and Vegetation Health in Central and South-Central Chile

Since 2010, Central and South-Central Chile have recorded abnormally low annual precipitation, resulting in over a decade-long megadrought. This water deficit has driven more severe wildfires, which begin earlier in the year, last longer, and burn over significantly larger areas. Past studies indicated wildland fires propagate following vegetation stress and under certain soil moisture conditions. Our work further investigated the drivers of the unprecedented wildfire that devastated Central and South-Central Chile in 2017 and 2023. To that end, we leveraged NASA Earth observations from space to explore the link between terrestrial variables and wildland fires. We first delineated the burnt extent using data from Landsat 9 Operational Land Imager 2 (OLI-2), along with the combined information from Terra + Aqua Moderate Resolution Imaging Spectroradiometer (MODIS). Next, we analyzed vegetation health based on the Normalized Difference Vegetation Index (NDVI) and evapotranspiration (ET) products of Terra MODIS. Furthermore, we examined soil moisture data from the Soil Moisture Active Passive (SMAP) mission. As the megadrought continues, we found greater anomalies and stress in vegetation indices across the region. We also identified certain pre-fire conditions in soil moisture and evapotranspiration in the days and months leading to the recent wildfires. We compared these findings against control areas that were not impacted by wildfires. Using satellite-based NASA Earth observations, we were able to provide insights into potential indicators of wildfire risk, which can augment future risk assessment and management efforts.

Benjamin D Goffin↗

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples, volume 1

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

Moore, N. R.↗

Ensemble Cancer Risk Model for Astronaut Risk Assessment

A new approach to NASA space radiation risk modeling has successfully extended the current NASA probabilistic cancer risk model to an ensemble framework able to consider sub-model parameter uncertainty (e.g. uncertainty in a radiation quality parameter) as well as model-form uncertainty associated with differing theoretical or empirical formalisms (e.g. combined dose-rate and radiation quality effects). Ensemble methodologies are already widely used in weather prediction, modeling of infectious disease outbreaks, and certain terrestrial radiation protection applications to better understand how uncertainty may influence risk decision-making. Applying ensemble methodologies to space radiation risk projections offers the potential to efficiently incorporate emerging research results, allow for the incorporation of future (including international) models, improve uncertainty quantification for underlying sub-models developed against sparse experimental data, and reduce the impact of subjective bias on risk projections. Moreover, risk forecasting across an ensemble of multiple predictive models can provide stakeholders additional information on risk acceptance if current health/medical standards cannot be met or the level of knowledge doesn’t permit a specific risk or exposure limit to be developed for future space exploration missions. In this work, ensemble risk projections implementing multiple sub-models of radiation quality, dose and dose-rate effectiveness factors, excess risk, and latency as ensemble members are presented. Initial consensus methods for ensemble model weights and correlations to account for individual model bias are discussed. In these analyses, the ensemble forecast compares well to results from NASA's current operational cancer risk projection model used to assess permissible exposure limits and permissible mission durations for astronauts. However, a large range of projected risk values are obtained at the upper 95th confidence level where models must extrapolate beyond available biological data sets; closer agreement is seen at the median + one sigma due to the inherent similarities in available models. Future work, including the addition of new models and methods for statistical correlation between predictive members are discussed to define alternate ways of thinking about risk and ‘acceptable’ uncertainty with respect to NASA’s current permissible exposure limits.

Lisa C Simonsen↗

Risk Assessment of Obstacle Collision for UAVs under Off-nominal Conditions

Enabling operations of unmanned aerial vehicles (UAVs) in low-altitude airspace demands the need of robust risk monitoring framework for assessing the safety of airspace, ground structures and people. As widespread applications emerge, the need of risk assessment becomes increasingly important for UAV flights beyond visual line-of-sight, especially subjected to off-nominal conditions introduced by component failures, degraded controllability or environmental disturbances such as wind gusts in an urban canyon. From a safety perspective, collision with obstacles can be detrimental not only to the vehicle and payload, but also to the structure and people on ground. Although it is safe to assume that approved UAVs would be equipped with collision avoidance systems, risk of collision which can be predicted for a flight trajectory even before the UAV encounters any obstacle is beneficial to resolve contingencies in its decision-making under off-nominal conditions. In this paper, a framework is presented for computing the risk of collision with obstacle based on a UAV’s predicted trajectory, proximity to static and dynamic obstacles, sub-system state-of-health and external wind conditions. The conditional probability of trajectory deviation is generated using a Bayesian Belief Network (BBN) based on on-board sensor measurements. Further, a kinematic 3-DOF model is implemented to compute deviation in UAV’s trajectory subjected to one case study of off-nominal condition i.e. wind gusts. Finally, the integrated risk factor is demonstrated on real data from experimental flights of an octocopter at NASA Langley Research Center, in presence of simulated obstacles and wind conditions. The proposed approach would enable risk-informed decision making process for timely mitigation of current and future unsafe events.

Bayesian network↗